(1) Field of the Invention
The present invention relates to a trajectory estimation method and a trajectory estimation apparatus, and a segmentation method, and particularly relates to a trajectory estimation method and a trajectory estimation apparatus, and a segmentation method which can accurately estimate, based on two or more images, trajectories of an object such as a person that moves changing shape on an image.
(2) Description of the Related Art
Conventionally, research and development for estimating trajectories on the image has been widely conducted. Particularly, the technique of estimating the trajectories of an object that changes shape such as a person is a basic technology commonly used for, for example, focus control and image quality improvement processing in a digital video camera or a digital still camera, and a driving safety support system for an automobile, or a collision avoidance control or warning using a robot.
The most common method for estimating trajectories is to estimate a motion vector based on similarity in pixel information, by providing, in an image, a block that is a partial region, and performing, on another image, a spatial search using the pixel information (pixel value) included in the block. The trajectories can be estimated by temporally concatenating such motion vectors.
However, according to this method, the motion vector is estimated based on the similarly in pixel value within the block. Thus, in the case of an image including a region such as a uniform region having no texture or a region having a striped pattern, it is not possible to accurately estimate the motion vector, thus resulting in an error to be included in the trajectories.
On the other hand, Non Patent Reference 2 describes a method for estimating more accurate trajectories. With this method, in the case of estimating the trajectories of a region such as a uniform region having no texture, the search is performed using only a robust point at which the pixel value is less likely to temporally change, such as a corner or an edge. This gives an advantage of allowing more accurate estimation of trajectories.    [Non Patent Reference 1] P. Anandan, “A computational Framework and an Algorithm for the Measurement of Visual Motion”, International Journal of Computer Vision, Vol. 2, pp. 283-310, 1989    [Non Patent Reference 2] Jianbo Shi and Carlo Tomasi “Good Features to Track”, IEEE Conference on Computer Vision and Pattern Recognition, pp. 593-600, 1994